Blog Archives

[Meta-]Blogging as young researchers

December 11, 2014
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[Meta-]Blogging as young researchers

Hello all, This is an article intended for the ISBA bulletin, jointly written by us all at Statisfaction, Rasmus Bååth from Publishable Stuff, Boris Hejblum from Research side effects, Thiago G. Martins from tgmstat@wordpress, Ewan Cameron from Another Astrostatistics Blog and Gregory Gandenberger from gandenberger.org.  Inspired by established blogs, such as the popular Statistical Modeling, […]

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Non-negative unbiased estimators

May 13, 2014
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Non-negative unbiased estimators

Hey hey, With Alexandre Thiéry we’ve been working on non-negative unbiased estimators for a while now. Since I’ve been talking about it at conferences and since we’ve just arXived the second version of the article, it’s time for a blog post. This post is kind of a follow-up of a previous post from July, where […]

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Parallel resampling in the particle filter

May 12, 2014
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Parallel resampling in the particle filter

Hey there, It’s been a while I haven’t written about parallelization and GPUs. With colleagues Lawrence Murray and Anthony Lee we have just arXived a new version of Parallel resampling in the particle filter. The setting is that, on modern computing architectures such as GPUs, thousands of operations can be performed in parallel (i.e. simultaneously) […]

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Moustache target distribution and Wes Anderson

March 31, 2014
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Moustache target distribution and Wes Anderson

Today I am going to introduce the moustache target distribution (moustarget distribution for brievety). Load some packages first. Let’s invoke the moustarget distribution. This defines a target distribution represented by a SVG file using RShapeTarget. The target probability density function is defined on and is proportional to on the segments described in the SVG files, […]

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Rasmus Bååth’s Bayesian first aid

January 23, 2014
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Rasmus Bååth’s Bayesian first aid

Besides having coded a pretty cool MCMC app in Javascript, this guy Rasmus Bååth has started the Bayesian first aid project. The idea is that if there’s an R function called blabla.test performing test “blabla”, there should be a function bayes.blabla.test performing a similar test in a Bayesian framework, and showing the output in a […]

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From SVG to probability distributions [with R package]

August 25, 2013
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From SVG to probability distributions [with R package]

Hey, To illustrate generally complex probability density functions on continuous spaces, researchers always use the same examples, for instance mixtures of Gaussian distributions or a banana shaped distribution defined on with density function: If we draw a sample from this distribution using MCMC we obtain a [scatter]plot like this one: Clearly it doesn’t really look […]

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Joint Statistical Meeting 2013

July 23, 2013
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Joint Statistical Meeting 2013

Hey, In a few weeks (August 3-8) I’ll attend the Joint Statistical Meeting in Montréal, Canada. According to Wikipedia it’s been held every year since 1840 and now gathers more than 5,000 participants! I’ll talk in a session organized by Scott Schmidler, entitled Adaptive Monte Carlo Methods for Bayesian Computation; you can find the session […]

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Path storage in the particle filter

July 12, 2013
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Path storage in the particle filter

Hey particle lovers, With Lawrence Murray and Sylvain Rubenthaler we looked at how to store the paths in the particle filter, and the related expected memory cost. We just arXived a technical report about it. Would you like to know more? Consider a particle filter with particles. At each step of the algorithm, positive weights […]

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Intractable likelihoods, unbiased estimators and sign problem

July 1, 2013
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Intractable likelihoods, unbiased estimators and sign problem

Hey all, We’re at the Big Data era blablabla, but the advanced computational methods usually don’t scale well enough to match the increasing sizes of datasets. For instance, even in a simple case of i.i.d. data and an associated likelihood function , the cost of evaluating the likelihood function at any parameter is typically growing […]

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Derivative-free estimate of derivatives

April 23, 2013
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Derivative-free estimate of derivatives

Hey, Arnaud Doucet, Sylvain Rubenthaler and I have just put a technical report on arXiv about estimating the first- and second-order derivatives of the log-likelihood (also called the score and the observed information matrix respectively) in general (intractable) statistical models, and in particular in (non-linear non-Gaussian) state-space models. We call them “derivative-free” estimates because they […]

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